Please use this identifier to cite or link to this item:
http://dx.doi.org/10.18419/opus-11149
Authors: | Dibak, Christoph |
Title: | Utilizing networked mobile devices for scientific simulations |
Issue Date: | 2020 |
metadata.ubs.publikation.typ: | Dissertation |
metadata.ubs.publikation.seiten: | 164 |
URI: | http://nbn-resolving.de/urn:nbn:de:bsz:93-opus-ds-111668 http://elib.uni-stuttgart.de/handle/11682/11166 http://dx.doi.org/10.18419/opus-11149 |
Abstract: | Numerical simulations on mobile devices create new applications supporting engineers and scientists in the field. Boosted by novel augmented reality devices, in-field analysis of complex systems allow engineers to make better decisions and predict the behavior of such systems by assuming different parameters before making risky and costly decisions. Mobile simulations are challenging as battery-powered mobile devices are only equipped with slow processors and are limited in energy resources. At the same time, mobile devices are only connected via wireless communication subjected to environmental conditions that might cause slow bandwidths or even disconnections to remote computing resources. Nevertheless, concepts presented in this thesis assume a distributed computation between mobile device and a powerful remote server. This thesis covers three major areas of the research field of mobile simulations. First, it provides concepts for distributed execution between server and mobile device in case of frequent disconnections. Second, it provides concepts using computationally less complex surrogate models for faster computation on the mobile device while still utilizing remote resources. Third, it provides concepts utilizing model order reduction for fast execution on mobile devices by pre-computing and adaptation of reduced models on a connected server. Evaluations show that concepts presented in this thesis significantly increase the performance of mobile simulations. In the case of disconnections, the number of deadline misses is reduced by 61 % while reducing the energy consumption by more than 74 % compared to a simplified approach. Concepts utilizing surrogate models speed-up the computation of the simulation by a factor of 6.5. Lastly, concepts utilizing model order reduction reduce the time for the computation of simulation results by a factor of 131 while using 73 times less energy for the specific test application. |
Appears in Collections: | 05 Fakultät Informatik, Elektrotechnik und Informationstechnik |
Files in This Item:
File | Description | Size | Format | |
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thesis-cd.pdf | 3,49 MB | Adobe PDF | View/Open |
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